/
__init__.py
30 lines (27 loc) · 1.08 KB
/
__init__.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
from maskrcnn_benchmark.data import datasets
from .giro import eval_giro
#from .coco import coco_evaluation
#from .voc import voc_evaluation
def evaluate(dataset, predictions, output_folder, **kwargs):
"""evaluate dataset using different methods based on dataset type.
Args:
dataset: Dataset object
predictions(list[BoxList]): each item in the list represents the
prediction results for one image.
output_folder: output folder, to save evaluation files or results.
**kwargs: other args.
Returns:
evaluation result
"""
args = dict(
dataset=dataset, predictions=predictions, output_folder=output_folder, **kwargs
)
# if isinstance(dataset, datasets.COCODataset):
# return coco_evaluation(**args)
# elif isinstance(dataset, datasets.PascalVOCDataset):
# return voc_evaluation(**args)
if isinstance(dataset,datasets.giro):
return eval_giro(**args)
else:
dataset_name = dataset.__class__.__name__
raise NotImplementedError("Unsupported dataset type {}.".format(dataset_name))